Modelling and evaluation of the Baseline Energy Consumption and the Key Performance Indicators in Technical University of Cluj‐Napoca buildings within a Demand Response programme: a case study

Cretu, Mihaela; Czumbil, Levente; Bargauan, Bogdan; Ceclan, Andrei; Berciu, Alexandru G.; Polycarpou, Alexis; Rizzo, R.; Micu, Dan D.

doi:10.1049/iet-rpg.2020.0096

Cited by 10 publications

(9 citation statements)

References 31 publications

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“…Step 2: Considering the load growth rate, the new loads, and the investments on DG units, the M load-generation scenarios for year t are calculated, as described in Section 3.1. For the M load-generation scenarios for year t, the NLP problem is solved using the commercial CONOPT solver [30] by minimising (23) subject to (4)- (22). Objective function (23) aims at minimising the energy curtailed from DG units, the curtailed load demand and the energy losses at year t. By solving the NLP problem, it is checked if there is a constraint violation, that is, it is examined if the distribution network operates within its nominal limits for year t. Furthermore, the annual energy losses, the curtailed load from demand response schemes, and the possible annual curtailed energy from the DG units are estimated.…”

Section: Multistage Dnp Methodsmentioning

confidence: 99%

“…For the M load-generation scenarios for year t, the NLP problem is solved using the commercial CONOPT solver [30] by minimising (23) subject to (4)- (22). Objective function (23) aims at minimising the energy curtailed from DG units, the curtailed load demand and the energy losses at year t. By solving the NLP problem, it is checked if there is a constraint violation, that is, it is examined if the distribution network operates within its nominal limits for year t. Furthermore, the annual energy losses, the curtailed load from demand response schemes, and the possible annual curtailed energy from the DG units are estimated. In case: (i) a constraint is violated, or (ii) the annual energy losses are higher than a threshold, or (iii) the annual curtailed load demand is higher than a threshold, or (iv) the energy curtailed from the DG units is higher than a threshold, proceed to Step 3.…”

Section: Multistage Dnp Methodsmentioning

confidence: 99%

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A multistage distribution network planning method considering distributed generation active management and demand response

Koutsoukis

Georgilakis

2021

IET Renewable Power Gen

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This paper proposes a multistage distribution network planning (DNP) method that considers multiple planning alternatives, the active management of distributed generation (DG) units and demand response in the context of active distribution networks (ADNs). Representative days are selected for the consideration of uncertainties related with load demand and renewable power generation, during the planning period. The proposed DNP method aims at minimising the net present value of the total investment and operational cost. The proposed DNP considers multiple planning alternatives, such as the reinforcement of existing substations and existing distribution lines, the installation of new distribution lines, and the installation of capacitors. Furthermore, the proposed DNP method incorporates the control capabilities of DG active and reactive power output and demand response schemes. A 24-bus distribution network and a 144-bus real world distribution network are used to validate the performance of the proposed method.

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Section: Multistage Dnp Methodsmentioning

confidence: 99%

Section: Multistage Dnp Methodsmentioning

confidence: 99%

A multistage distribution network planning method considering distributed generation active management and demand response

Koutsoukis

Georgilakis

2021

IET Renewable Power Gen

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Section: Overview Of the Implemented Demand Response Systemmentioning

confidence: 99%

“…Figure 2 shows an overview of the aggregated system that includes a series of data information and equipment for the centralized management of several pilot sites. As main functionalities and subsystems, the following are highlighted [52]: Figure 2 shows an overview of the aggregated system that includes a series of data information and equipment for the centralized management of several pilot sites. As main functionalities and subsystems, the following are highlighted [52]: 1.…”

mentioning

confidence: 99%

“…As main functionalities and subsystems, the following are highlighted [52]: Figure 2 shows an overview of the aggregated system that includes a series of data information and equipment for the centralized management of several pilot sites. As main functionalities and subsystems, the following are highlighted [52]: 1. Market emulation (ME) unifies information from the energy market (from electricity distribution system operator (DSO), electricity transmission system operator (TSO), energy suppliers, aggregators, etc.)…”

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confidence: 99%

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Custom Outlier Detection for Electrical Energy Consumption Data Applied in Case of Demand Response in Block of Buildings

Jurj

Czumbil

Bargauan

et al. 2021

Sensors

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The aim of this paper is to provide an extended analysis of the outlier detection, using probabilistic and AI techniques, applied in a demo pilot demand response in blocks of buildings project, based on real experiments and energy data collection with detected anomalies. A numerical algorithm was created to differentiate between natural energy peaks and outliers, so as to first apply a data cleaning. Then, a calculation of the impact in the energy baseline for the demand response computation was implemented, with improved precision, as related to other referenced methods and to the original data processing. For the demo pilot project implemented in the Technical University of Cluj-Napoca block of buildings, without the energy baseline data cleaning, in some cases it was impossible to compute the established key performance indicators (peak power reduction, energy savings, cost savings, CO2 emissions reduction) or the resulted values were far much higher (>50%) and not realistic. Therefore, in real case business models, it is crucial to use outlier’s removal. In the past years, both companies and academic communities pulled their efforts in generating input that consist in new abstractions, interfaces, approaches for scalability, and crowdsourcing techniques. Quantitative and qualitative methods were created with the scope of error reduction and were covered in multiple surveys and overviews to cope with outlier detection.

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Energy Pulse: Competitive and Accessible Application for Monitoring Electricity Consumption

Berciu,

Dulf,

Jurj

et al. 2024

Springer Proceedings in Mathematics &Amp; Statistics

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Modelling and evaluation of the Baseline Energy Consumption and the Key Performance Indicators in Technical University of Cluj‐Napoca buildings within a Demand Response programme: a case study

Cited by 10 publications

References 31 publications

A multistage distribution network planning method considering distributed generation active management and demand response

A multistage distribution network planning method considering distributed generation active management and demand response

Custom Outlier Detection for Electrical Energy Consumption Data Applied in Case of Demand Response in Block of Buildings

Energy Pulse: Competitive and Accessible Application for Monitoring Electricity Consumption

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